Litcius/Paper detail

Forest Fire Detection and Prediction from image processing using RCNN

Abhay Chopde, Ansh Magon, Shreyas Bhatkar

2022Proceedings of the World Congress on Civil, Structural, and Environmental Engineering17 citationsDOIOpen Access PDF

Abstract

Forests are the most important part of terrestrial life as they provide shelter to 80% of terrestrial life and provide them with food as well. Forest fires are a serious threat to flora and fauna followed by deforestation. Various preventive measures are taken to avoid such incidents from taking place still, many such incidents happen every year causing long term damage to surrounding biology, environment, and wildlife. This paper proposes a large-scale monitoring system and deep learning-based forest fire detection model that can detect forest fires from video frames captured by UAV drones. The proposed CNN model successfully detects forest fires with 97.29% accuracy. This will help to control the forest fires before they get out of control.

Topics & Concepts

Computer scienceArtificial intelligenceImage processingFire detectionPattern recognition (psychology)Computer visionImage (mathematics)EngineeringArchitectural engineeringFire Detection and Safety Systems
Forest Fire Detection and Prediction from image processing using RCNN | Litcius